Cognitive Carpentry: A Blueprint for how to Build a Person
Cognitive Carpentry: A Blueprint for how to Build a Person
A Reasoning Model Based on the Production of Acceptable Arguments
Annals of Mathematics and Artificial Intelligence
Games That Agents Play: A Formal Framework for Dialogues between Autonomous Agents
Journal of Logic, Language and Information
Argumentation schemes and generalisations in reasoning about evidence
ICAIL '03 Proceedings of the 9th international conference on Artificial intelligence and law
Towards a formal account of reasoning about evidence: argumentation schemes and generalisations
Artificial Intelligence and Law - Law, logic and defeasibility
Try to see it my way: modelling persuasion in legal discourse
Artificial Intelligence and Law
A dialogue mechanism for public argumentation using conversation policies
Proceedings of the 7th international joint conference on Autonomous agents and multiagent systems - Volume 1
Towards Context Sensitive Defeasible Rules
Computational Logic in Multi-Agent Systems
Contextual Extension with Concept Maps in the Argument Interchange Format
Argumentation in Multi-Agent Systems
Dialogue games that agents play within a society
Artificial Intelligence
Argumentation scheme and shared online diagramming in case-based collaborative learning
CSCL'09 Proceedings of the 9th international conference on Computer supported collaborative learning - Volume 1
Review: representing and classifying arguments on the semantic web
The Knowledge Engineering Review
IJCAI'11 Proceedings of the Twenty-Second international joint conference on Artificial Intelligence - Volume Volume Three
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Argumentation schemes are patterns of non-deductive reasoning that have been the focus of extended study in argumentation theory. They have also been identified in computational domains including multi-agent systems as holding the potential for significant improvements in reasoning and communication abilities. By focusing on models of natural language argumentation schemes, and then building formal systems from them, direct implementation in multi-agent environments becomes a possibility. The formal, representational and implementational details are presented here, along with results that demonstrate not only advantages of flexibility, scope, and knowledge sharing, but also of computational efficiency.